MoorAI vs HiddenLayer
Last updated
HiddenLayer’s coding-agent hooks ask its detection service for a verdict. MoorAI’s hook reaches the verdict on the device. HiddenLayer’s product for coding agents is Agent Harness Security: “As organizations adopt AI coding agents such as Claude Code, Cursor, and GitHub Copilot, the harness itself becomes a new security boundary.” (hiddenlayer.com, Agent Harness Security) Its architecture page says how it reaches them: “The coding agent’s hook system calls Agent Harness Security at each gate point, like prompt submission and tool use.” (HiddenLayer docs, Agent Harness architecture) MoorAI is a PreToolUse hook inside the coding agent and a Model Context Protocol (MCP) stdio proxy in front of the tool servers. It reads the prompt, the file read into context, the shell command and the MCP arguments and results, and coaches, masks or blocks on what it finds.
The two overlap closely on coding agents. Both gate the prompt, the tool call and the tool result; both can block, redact or only record; both scan what comes back from a tool for injection. HiddenLayer: “It can redact sensitive information before a model sees it, steer agents away from poisoned tool responses, and stop unsafe actions before they pose a risk.” (HiddenLayer, Agent Harness Security launch) The difference is where the content goes. HiddenLayer’s data-handling page says of its SaaS deployment: “Detection data, including prompts and responses, is securely sent through the API for detection and visibility within the HiddenLayer Console.” (HiddenLayer docs, data handling) Its Hybrid and Self-Hosted deployments keep that content in your own network. MoorAI decides against a 77-threat matrix and by default sends only category · risk · keyed one-way hash (plus the login and hostname, which the console pseudonymises on arrival).
HiddenLayer covers far more of the AI estate than MoorAI does. Its platform spans discovery, model supply-chain scanning, attack simulation and runtime security for AI applications and agents, and coding agents are one part of it. MoorAI governs coding agents and their MCP traffic. The rows where HiddenLayer covers more ground are further down.
Three things this page does not state. (1) Which deployment modes Agent Harness Security supports. The data-handling page describes SaaS, Hybrid and Self-Hosted for Runtime Security; the Agent Harness deployment guide shows a HiddenLayer API region as the platform URL and does not say whether the plug-in runs against a self-hosted deployment. (2) The plug-in itself. HiddenLayer’s guide says “Obtain the plug-in from HiddenLayer. Contact your HiddenLayer sales representative or support.” (HiddenLayer docs, Agent Harness deployment) We did not inspect it, and its developer portal sits behind a login. (3) Pricing. We found no public price list. Every HiddenLayer statement below is quoted from HiddenLayer’s own site or docs, and the page is named.
The core difference is where the content is judged: by a detection service the hook calls, or on the machine the agent runs on.
/detection/v2/claude-code/pre-tool-use. (HiddenLayer docs, Agent Harness architecture) With Hybrid or Self-Hosted that service runs on infrastructure you operate; with SaaS it is HiddenLayer’s. MoorAI’s engine runs inside the hook process on the developer’s machine, and connects to nothing to reach a verdict. For claude -p in CI or an Agent SDK service in a container, MoorAI’s server mode runs the same hook.Where MoorAI holds ground HiddenLayer does not
These rows follow from judging content on the machine, and from coding-agent detectors HiddenLayer does not describe. HiddenLayer marks are unconfirmed where its public material is silent.
Scroll sideways →
| MoorAI | HiddenLayer | |
|---|---|---|
| Coding-agent verdict computed on the developer’s machine, with nothing sent anywhere to decide | ✓ | ✗the hook calls the detection service |
| Prompts and code stay on the machine without running your own detection service | ✓only category, risk and keyed hash (plus login and hostname, pseudonymised on arrival) leave by default | ◐kept in your network with Hybrid or Self-Hosted; sent with SaaS |
| Hooks for Codex CLI and Gemini CLI | ✓pre-tool hooks; not yet validated against the live agents | —published tables cover Claude Code, Cursor, GitHub Copilot |
| Flags a proxy plus CA override that reroutes the agent’s traffic | ✓transit-override detection | —not in public material |
| Flags an agent pointed at a model endpoint that is not on the allow-list | ✓model-endpoint allow-list | — |
| Knocks an approved MCP server back to pending when its config changes | ✓rug-pull detection | — |
| Reports the agent’s rules files leaving the device, by fingerprint | ✓ | — |
| Flags a risky action aimed at something the user’s request never named | ✓intent alignment; lexical, keyed hashes | — |
| Scans the local files an MCP call names, as if the agent had read them | ✓hook and stdio proxy | — |
| Coaches on a device that is not enrolled, and never blocks there | ✓ | — |
| Open source, so the data claim can be checked in code | ✓agent MIT | ◐integrations Apache-2.0; agent plug-in not published |
| Free to start and to enforce, without talking to sales | ✓agent free; console free to 200 users | ✗no public pricing; demo-led |
Where HiddenLayer covers ground MoorAI does not
This list is longer. HiddenLayer secures models, AI applications and agents across their lifecycle; coding agents are one module. MoorAI covers coding agents and their MCP traffic, and does not touch models.
Scroll sideways →
| MoorAI | HiddenLayer | |
|---|---|---|
| Scans model files for malicious code, backdoors and vulnerable dependencies | ✗ | ✓Model Scanner |
| Attack simulation: testing AI systems for jailbreaks, injection and prompt leakage | ✗ | ✓ |
| Discovery of models and agents across cloud accounts, repos, endpoints and pipelines | ◐on-device AI bill of materials only | ✓ |
| Runtime protection for AI applications and agentic workflows beyond coding agents | ✗ | ✓ |
| An agent run reconstructed as one replayable session | ✗by design: no content leaves the device | ✓may not be enabled for every tenant yet |
| A protection mode on every evaluation: as configured, strengthened, or observed only | ✗ | ✓ |
| Visibility gates in Claude Code for tool failure, stop, subagent stop and pre-compact | ✗ | ✓ |
| Detection that can run entirely inside your own network, with no vendor service | ✓on the device | ✓Enterprise Self-Hosted |
Same capability, different mechanism
Both products do each of these, so the table describes how rather than scoring.
Scroll sideways →
| MoorAI does it by… | HiddenLayer does it by… | |
|---|---|---|
| Stopping a coding agent’s action before it runs | A PreToolUse hook in the agent’s own process, validated end to end on Claude Code. Codex CLI, Copilot CLI, Gemini CLI and Cursor block through their own pre-tool hooks and are not yet validated against the live agents. An MCP stdio proxy enforces for any host that launches a stdio MCP server. | A plug-in that installs hooks in Claude Code, Cursor and GitHub Copilot; each hook calls the detection API and receives the decision “in the format the agent understands.” (HiddenLayer docs, Agent Harness architecture) |
| Redacting instead of blocking | The mask action rewrites a secret or PII span to [MOORAI:<tier>:<8 letters>], derived from the keyed hash, in the tool input or tool result, and lets the call proceed. Built from Claude Code’s hooks reference and not yet observed in a live session. |
A redact decision applied at the gates that allow it; “Where a gate cannot apply redaction, a redact decision is escalated to block rather than letting sensitive content through.” (HiddenLayer docs, Agent Harness architecture) |
| Handling a poisoned tool result | A PostToolUse scan of what comes back from shell, MCP, web and sub-agent calls, within a 64 KB window. A policy “ask” there becomes advisory context telling the model to treat the output as data, not instructions. | A post-tool gate that can block, redact or detect before output reaches the model, and “corrective context” to steer the agent away. (HiddenLayer, Agent Harness Security launch) |
| Catching a bad package install | An offline slopsquatting classifier that gates installs of near-miss and hallucinated package names against a curated popular-package list and a known-bad set. | Detection of “malicious or unexpected dependency installs” (HiddenLayer docs, Agent Harness overview); the method is not described. |
| Rolling out to a fleet | A .dmg or Homebrew cask for macOS, a signed setup for Windows, a one-line install script or a Claude Code plugin, with Jamf or Intune writing the enrollment file. In server mode, a Dockerfile registers the hooks in Claude Code’s managed settings. |
“Deploy using an MDM application, like Jamf or Microsoft Intune.” (HiddenLayer docs, Agent Harness deployment), then hl commands to configure the plug-in and install the hooks. |
MITRE ATLAS, as documented. In our reading of vendor material against the 76 ATLAS techniques tagged Agentic AI, HiddenLayer’s published material documents 14 of the 76 (read 1 October 2026), 7 of them with a limit the vendor states. Several cells come from attack simulation and discovery, which test for or inventory a technique rather than stop it at runtime, and one from model scanning. That counts what the documentation says, not a test of the product. The method and every quote behind the number are in MITRE ATLAS agentic-technique coverage.
Where MoorAI is stronger. An on-device verdict, by default, with coding-agent depth. Content is judged inside the hook on the developer’s machine, with no detection service to run or reach; the console receives no content; and proxy overrides, model endpoints, MCP servers that change after approval, rules-file leaks, actions aimed outside the user’s request and the files an MCP call names are each checked there. MoorAI also hooks Codex CLI and Gemini CLI. The agent is MIT and free to enforce up to 200 users.
Where HiddenLayer is stronger. The AI estate beyond coding agents, and honest enforcement reporting. Model files scanned for malicious code and backdoors; attack simulation; discovery across cloud accounts, repos and pipelines; runtime protection for AI applications and agentic workflows; sessions reconstructed for replay; and a protection mode recorded on every evaluation so an auditor can see where an agent platform limited enforcement. If the job is securing models and AI applications across their lifecycle, HiddenLayer is the larger product and MoorAI is not one.
Which to run where. Run HiddenLayer where the question spans the AI estate: models in the supply chain, AI applications in production and coding agents under one console, with the detection service in HiddenLayer’s cloud or your own. Run MoorAI on developer machines and CI runners where the question is what a coding agent is about to read, run or send, and where the verdict should be reached on the machine with no content leaving it. Both register Claude Code hooks, so on one machine they would run side by side in the same hook events; nothing in either’s public material says they conflict, and we have not run them together.
Questions about MoorAI and HiddenLayer
Does HiddenLayer’s coding-agent plug-in send prompts to HiddenLayer?
It depends on the deployment. HiddenLayer’s data-handling page says Enterprise SaaS sends detection data, including prompts and responses, through the API; Enterprise Hybrid can keep prompt and response data local if console visibility is not required; and Enterprise Self-Hosted transmits no customer data outside your network. In each case the agent’s hook calls a detection service for the verdict. MoorAI reaches its verdict on the device and by default sends only a category, a risk level and a keyed one-way hash (plus the login and hostname, which the console pseudonymises on arrival).
Which coding agents does HiddenLayer Agent Harness Security cover?
HiddenLayer names Claude Code, Cursor and GitHub Copilot, and publishes a gate-by-gate table for each showing where it can block, redact or only record. MoorAI hooks Claude Code, validated end to end, and Codex CLI, Copilot CLI, Gemini CLI and Cursor, which are not yet validated against the live agents.
Does MoorAI replace HiddenLayer, or the other way round?
No. HiddenLayer secures models, AI applications and agents with discovery, model scanning, attack simulation and runtime security. MoorAI does none of that beyond coding agents. MoorAI inspects what a coding agent’s actions contain and coaches, masks or blocks on the device, with no content sent to a vendor.
Can I try HiddenLayer’s coding-agent protection without talking to sales?
HiddenLayer’s deployment guide says to obtain the plug-in through a HiddenLayer sales representative or support, and we found no public pricing. The MoorAI agent is MIT-licensed and free, and the MoorAI console is free up to 200 users.
Who backs HiddenLayer?
On 2 September 2026 HiddenLayer announced a $100 million Series B led by Delta-v Capital, with participation from Ten Eleven Ventures, Morgan Stanley, M12 (Microsoft’s venture fund) and Booz Allen Ventures.
HiddenLayer capabilities are taken from HiddenLayer’s own published material, checked on 1 October 2026: Agent Harness Security, the Agent Harness Security launch, the Series B announcement, AI Runtime Security, Model Scanning, AI Attack Simulation, AI Discovery, and the HiddenLayer docs pages Agent Harness overview, architecture, deployment, Agentic Runtime Security and data handling. Every quoted phrase is HiddenLayer’s. ◐ = partial: present but narrower than the other column. — = unconfirmed, not necessarily absent. MoorAI marks reflect shipped capability: hook enforcement is validated end to end on Claude Code; Codex, Copilot CLI, Gemini CLI and Cursor block through their own pre-tool hooks and are not yet validated against the live agents. The agent is MIT and runs on macOS, Windows and Linux; the console is source-available under the Elastic License 2.0 and free up to 200 users. HiddenLayer is a trademark of its owner; this page is independent and is not affiliated with or endorsed by HiddenLayer. Both products change, so check specifics against current documentation.